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KPMG U.S. examined Tether’s books and even counted its gold bars as the $180 billion USDT issuer said it completed its long-promised financial audit.

The official government website for requesting free credit reports from the three major credit bureaus just got a makeover.
A sharp-eyed Reddit user called attention to a major refresh of the “look and layout” of AnnualCreditReport.com, urging consumers to become familiar with the new design so they don’t fall victim to credit scams.

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Before the changes were implemented in late July, the site had been due for a redesign. One blog even commented in May that the “the site looks dated (federal-government dated), which is actually a good sign that it’s the real thing.”
AnnualCreditReport.com has a totally new look since the update, so make sure you’re navigating to the correct URL when using it.

The old AnnualCreditReport.com design (top) and the new version of the site (bottom).
The website was created by federal law in 2004, and at the time, online credit report requests through the website were annual, as the site’s name suggests. (Since 2020, consumers have been able to request free copies of their credit reports from each of the three agencies on a weekly basis.)
Over the years, the website has been edited and updated, but the latest revisions represent an overhaul to the design. According to Benjamin Corb, senior vice president for strategy and public affairs at the Consumer Data Industry Association, the new version is considered the third iteration of the website.
“This is now a refurbish of a refurbish… So it just felt like the right time,” he says.
The association says there wasn’t a particular catalyst — like a specific consumer complaint or a technical vulnerability — that led to the update. But Americans accessing AnnualCreditReport.com on their phones or tablets will particularly benefit.
“The previous website, it worked when looking on mobile,” Corb adds. “But this refresh is really designed to help give the user a better experience, particularly if they’re going on a mobile phone.”
What you need to know about the AnnualCreditReport.com redesign
Archives of the website show that the changes were made sometime between July 26 and July 28.
The rollout was quiet. “We didn’t put up billboards or anything to say that we had refreshed the website,” Corb says.
AnnualCreditReport.com is copyrighted by Central Source LLC, which was created by Equifax, Experian and TransUnion. Money was unable to reach Central Source LLC for comment on the changes and the goals of the refresh.
As the Reddit user mentioned, the new website appears functionally similar to previous versions. Users are directed to a form where they can input information including their name, address, Social Security number and birthdate, then are directed to external credit-reporting-agency webpages where the credit report requests are completed.
“We’ve simplified the report request flow to reduce the number of pages that you have to do in order to go through the process,” Corb says. “All of the data that is there is still the same data that you would get from the credit bureaus.”

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The updated website is faster and sleeker. The homepage features new text, now touting, “For over 20 years, we’ve helped people get their free credit reports safely and easily.” It emphasizes privacy, and the site has been modified in several places to clarify that credit reports can now be requested weekly.
Site copy and FAQs have been replaced, alongside the addition of new visual elements and modern graphics.
“It’s updating what we had before,” Corb says. “It’s the same consistent messaging that we’ve always had.”
Some of the text on the website appears identical to copy on existing webpages. For example, there are exact text matches in the new site’s “Fixing mistakes on your credit report” page and this 2016 Experian guide. Corb was open that the site includes articles “from the industry” that provide background on topics like credit reports, credit scores, identity theft and managing debt.
Are credit reports changing?
The credit reports produced for people who use the site are unaffected by the changes. In a statement, an Equifax spokesperson notes that the company improved the credit reports it delivers through AnnualCreditReport.com last year but confirmed that those changes were separate from the late-July refresh of the three-bureau website.
“Color-coded sections and easy-to-read graphics were added [to reports] to replace lengthy pages of text and to give consumers a comprehensive look at their current and past credit activity,” the Equifax spokesperson wrote in an email.
Equifax declined to comment on the site refresh itself, and Experian did not respond to our requests for comment. TransUnion directed questions to the Consumer Data Industry Association.
Users should find that the new website offers a largely familiar experience. The most important takeaway: To protect yourself from identity theft and upcharges, always make sure to use the correct URL (AnnualCreditReport.com) and avoid lookalike sites.
It’s too early gauge how consumers are responding to the new site, but the credit reporting agencies are confident it’s an improvement.
“We’re really happy with the new website and the look and feel, and hope consumers are able to use it for a lot of valuable reasons,” Corb says.

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Doing well at something is not the same as wanting it. Plenty of people are steady at their jobs and still feel hollow at the end of the day. Nothing looks wrong from the outside. Colleagues respect you, the pay lands on time, and you handle whatever gets thrown your way. What builds underneath is harder to name.
A dullness sets in, or a restlessness, or the sense that you’re watching your own work from across the room. It doesn’t mean everything needs to be torn down. Often it just means you’ve stopped growing, and once that happens, what counts as worthwhile work quietly changes shape. 
When work shifts
There is usually no announcement. One day the tasks that once demanded your full attention take almost nothing out of you. Some people notice their focus sliding away from the work and toward the people around it. Wanting to mentor, listen, and help someone untangle a problem tells you something real about where your attention wants to go.
This lands hard in teaching. Class sizes and schedules leave little room for one student who needs an hour, and administrative work swallows the time you’d rather give them. Many educators respond by shifting from a teacher to a counselor, a role built around emotional and social support instead of lesson plans. The work runs deeper with each student and puts their wellbeing at the center of the day.
Changes like this rarely announce themselves loudly. They start as a small nudge you can brush off. Ignoring it gets harder as the months go by.
What purpose feels like
Most of the time it arrives quietly. A small exchange leaves you feeling like you were actually needed. You break down something complicated and watch it land. You steady someone who was spiraling. You point a person toward a way forward when they couldn’t see one. The tiredness afterward sits differently from the kind that flattens you.
Notice when you feel most switched on. Some people run best on targets, numbers, and systems that click into place. Others come alive guiding, backing someone up, keeping them going. Neither ranks above the other. They simply pull from different places.
Work that feels worthwhile usually reflects what you already care about. Value connection, trust, and steady growth, and a people-centered job will sit better than one measured purely in output. Perfection isn’t the goal. Honesty is.
Clues in your strengths
Patterns show up long before certainty does. Consider what people bring to you without being asked. Do friends start unloading before they’ve taken their coat off? Do colleagues mention how calmly you explain things? Are you the steady one while everyone else scatters like startled pigeons?
Pay attention to that. Support and guidance roles tend to grow out of qualities like these:

Patience when someone needs time
Empathy without absorbing everything
Clear communication
Real listening
Steadiness under pressure
Encouragement that doesn’t take over

Calling these soft undersells them. They carry weight because they help actual people get through difficult stretches. Technical knowledge can be added later. A steady, caring way with people is harder to teach, and having it already puts you closer to a new path than you might assume.
Why helping can grow
Roles built around helping tend to keep demanding more of you as a person. There’s no clocking in and ticking off a list. You get better at hearing what someone isn’t saying, at answering with more care, at reading people accurately. Growth like that outlasts any promotion.
Your motivation changes shape too. Pay and status stop being the whole scoreboard, and impact starts to matter. Did that person feel understood today? Did something hard get lighter because you were there? Questions like those keep the work from going flat.
None of which makes it effortless. The emotional load is real. Boundaries hold everything together, and so does proper rest. Choose a helping career with clear eyes, because meaning doesn’t cover lunch, sleep, or a life outside the job.
Testing the next step
Nothing has to be decided by next Tuesday. Small, low-stakes experiments beat dramatic leaps almost every time. Walk around in the shoes before entering the marathon.
Try a few of these:

Talk to someone doing the job now
Ask about ordinary days, not the highlights
Volunteer somewhere support is the point
Shadow a professional if you can arrange it
Sign up for one course
Note down what leaves you energized

Each one separates the imagined version from the real one. Occasionally a role loses its shine once you hear what the hours involve. Just as often, seeing it up close confirms what you suspected.
Stay curious rather than urgent. No contract is being signed. You’re collecting evidence, and evidence beats panic when a career decision is on the table.
Making change less scary
Fear arrives even when the change is a good one. Money, timing, family obligations, the thought of being a beginner again. None of that is irrational. Your brain is doing its job, protecting you, just with more theatrics than the situation calls for.
Size is usually the problem. “Should I change my whole life” is an unanswerable question, and holding it in your head produces nothing but dread. Narrow it until it becomes something you can act on this month. Build savings first. Find out what training actually requires. Set a six-month window and see what you learn inside it.
The fear rarely disappears entirely, and it doesn’t need to. It shrinks once the decision stops being one enormous leap and becomes a series of ordinary moves you can reverse if they don’t work.
Choosing a better fit
Borrowed definitions of success cause most of the trouble. Looking impressive while feeling depleted is a trade that stops paying off quickly. Your own version asks harder questions. Does this line up with what you care about? Does it draw on what you’re actually good at? Could you do it without performing a version of yourself all day?
Alignment matters more than ambition here. The goal is work that fits, that spends your energy well, that lets you be useful without straining for it.
That pull toward something more meaningful deserves attention rather than dismissal. Look into it. Give it time. The full map isn’t required. One honest step forward is usually enough to start.
The post Signs You’re Ready for a More Purposeful Career appeared first on Addicted 2 Success.

Google is rolling out Gemini 3.7 Flash, a new version of its workhorse AI model that puts coding, agentic workflows and knowledge work at the center of the upgrade — while temporarily cutting API prices in half.The release arrives just three weeks after the release of Gemini 3.6 Flash, an unusually short turnaround that Google attributes to developer feedback and algorithmic improvements. For enterprise developers, the more consequential story may be the combination of those intelligence gains with lower inference costs: through the end of 2026, Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens.Starting Jan. 1, 2027, pricing rises to $1.50 per million input tokens and $7.50 per million output tokens. That means the current discount is temporary, but it gives teams deploying high-volume coding and business agents several months to evaluate whether Google’s claimed reductions in retries and manual oversight translate into lower total operating costs.The launch also underscores Google’s rapid iteration on its Flash line while its next flagship Pro model remains absent. Google did not provide a release date for Gemini 3.5 Pro with Thursday’s announcement, Reuters reported, despite the model having previously been described as undergoing partner testing. Axios similarly noted that 3.7 Flash arrives before the anticipated Pro release.A three-week upgrade focused on getting work doneGoogle describes Gemini 3.7 Flash as its “most intelligent workhorse model yet for coding and agents.” The company says the model is better at adapting when it encounters roadblocks, clarifying intent when necessary and following instructions with greater fidelity.Those improvements matter beyond benchmark scores. In an enterprise coding agent, a model that makes fewer unnecessary changes, recovers from errors and executes multi-step plans more reliably can reduce the number of human interventions needed to complete a task. The same principle applies to business agents operating across documents and applications, where an incorrect tool call or poorly interpreted instruction can derail an otherwise useful workflow.Google says 3.7 Flash “thinks more diligently,” applying more effort to multi-step planning and tool calls. Its stated goal is more disciplined execution with fewer retries and less manual supervision.That represents an interesting evolution from Gemini 3.6 Flash. Google’s developer documentation described 3.6 as reducing reasoning steps, conversational turns and tool calls compared with earlier models while attempting to limit execution-loop spiraling. With 3.7, the emphasis shifts toward putting sufficient effort into planning while improving the quality of execution — potentially a more useful optimization than simply minimizing the number of steps an agent takes.Google DeepMind said in a post accompanying the release that 3.7 Flash shows gains in debugging and issue resolution, generates more functional web layouts and applications with fewer prompts, and improves reasoning and accuracy on real-world business workflows.Coding gains are substantial, but not universalGoogle’s benchmarks show a large generational improvement in several software engineering tests.On FrontierCode 1.1 Main, which measures production code quality, Gemini 3.7 Flash scores 43.6%, up from 34.4% for Gemini 3.6 Flash. That also narrowly exceeds the 42.7% Google reports for Claude Sonnet 5 and 41.3% for GPT-5.6 Terra.On DeepSWE v1.1, a long-horizon software engineering evaluation, 3.7 Flash reaches 65.3%, compared with 49.0% for its predecessor. GPT-5.6 Terra remains ahead at 69.6% in Google’s table.Web development shows another notable gain. Gemini 3.7 Flash receives an Elo score of 1588 on Code Arena, versus 1538 for 3.6 Flash, 1541 for Claude Sonnet 5 and 1523 for GPT-5.6 Terra. Google says the new model can produce more functional layouts and feature-complete applications in fewer prompts while more closely following reference screenshots, images and design systems.The broader benchmark table is more mixed, which is important for enterprises evaluating the model against particular workloads rather than looking for a single “best” model.Gemini 3.7 Flash scores 85.8% on Terminal-bench 2.1, compared with 87.4% for GPT-5.6 Terra. Terra also leads Google’s comparisons on Terminal-bench 3.0 and OSWorld-2.0. Claude Sonnet 5 leads the Agent’s Last Exam multimodal desktop and operating-system tasks with a 33.3% pass rate, versus 26.3% for Gemini 3.7 Flash.In other words, Google’s own results do not show 3.7 Flash universally displacing higher-priced competitors. They instead suggest a model that has become substantially more competitive in coding and agent workloads while occupying a lower price tier.Enterprise workflows may be the more important testThe gains extend beyond software development.On AutomationBench, which Google describes as measuring enterprise workflow automation, Gemini 3.7 Flash scores 30.4%, up sharply from 17.0% for 3.6 Flash. Google’s table lists Claude Sonnet 5 at 10.7% and GPT-5.6 Terra at 23.6%.The model also reaches 34.0% on GDP.PDF, an evaluation of complex PDF comprehension, compared with 22.0% for 3.6 Flash, 28.0% for Claude Sonnet 5 and 24.7% for GPT-5.6 Terra.That combination is relevant for enterprise agents because many practical deployments require more than generating text or code. An agent may need to interpret a long report, identify relevant information, decide which tool to invoke, update another system and produce a document for a human reviewer. Reliability across that chain can matter more than performance on an isolated reasoning benchmark.Google is putting that thesis into practice with Gemini Spark. Google AI Pro and Ultra subscribers can use 3.7 Flash in Spark, the company’s personal AI agent. Google says the upgrade improves Spark’s knowledge work and tool use across Google Workspace applications, including workflows that consolidate files, draft emails and update status documents.For enterprises, 3.7 Flash is also available through the Gemini Enterprise Agent Platform and Gemini Enterprise app.Price becomes part of the model competitionGemini 3.7 Flash’s introductory pricing is a notable bid to embed the model into enterprise workflows.Until Dec. 31, developers pay $0.75 per million input tokens and $3.75 per million output tokens. Context caching costs $0.075 per million tokens during the introductory period. Google says standard prices will double on Jan. 1, 2027, to $1.50 for input and $7.50 for output, with context caching rising to $0.15.For comparison, Gemini 3.6 Flash’s standard API pricing is $1.50 per million input tokens and $7.50 per million output tokens. Google’s benchmark table lists Claude Sonnet 5 at $2 and $10, respectively, while GPT-5.6 Terra is listed at $2 and $12.The economics become more pronounced for autonomous agents because a single user request can produce a long sequence of model calls, reasoning tokens and tool interactions. A model that costs less per token but requires substantially more retries may not ultimately be cheaper. Conversely, Google’s combination of lower introductory token pricing and claimed improvements in first-pass accuracy could materially change the cost of running high-volume coding or document-processing agents if those gains carry over to production.That is the metric enterprise teams will ultimately need to test: not price per million tokens in isolation, but cost per successfully completed task.Google’s AI shake-up raises the stakes for GeminiGemini 3.7 Flash arrives amid a broader debate over whether Google is losing ground at the AI frontier. The company has not released Gemini 3.5 Pro, despite saying in May that the flagship model would arrive the following month. By July, Google said it remained in partner testing and would become broadly available when ready; Thursday’s announcement offered no further timetable. Google’s latest released general-purpose Pro model therefore remains Gemini 3.1 Pro, introduced in February. Reuters reported in July that Gemini 3.5 Pro missed its original target after falling short of internal goals, particularly in coding, even as Google began training what it calls its most ambitious model yet, Gemini 4.The delay coincides with a major overhaul of Google’s AI leadership announced last week. Google DeepMind co-founder and Nobel Prize Winner Demis Hassabis has relinquished day-to-day control of the company’s famed DeepMind AI division to become its chair and, simultaneously, to take on the role of Alphabet’s chief scientist.Meanwhile, former DeepMind CTO Koray Kavukcuoglu now runs the unit as a senior vice president reporting directly to CEO Sundar Pichai. Kavukcuoglu controls Gemini model development, frontier research, the Gemini app and developer teams—effectively consolidating the full Gemini chain under a more product-focused operator. Chief scientist Jeff Dean, Gemini co-lead Oriol Vinyals, Quoc Le and Sanjay Ghemawat left to establish the research startup Discovery Loop. Those exits followed Gemini co-lead Noam Shazeer’s move to OpenAI and Nobel Prize-winning AlphaFold scientist John Jumper’s departure for Anthropic. Reuters reported that internal disagreements, constrained compute allocation and Google’s bureaucracy contributed to slower releases and weaknesses in coding.Outside interpretations range from organizational repair to a more fundamental retreat. SemiAnalysis has argued that Google is increasingly prioritizing the highly profitable business of supplying cloud infrastructure to AI companies—including Gemini competitors—over keeping its own models at the absolute frontier. That analysis also claimed Google had effectively canceled 3.5 Pro, although Google has not confirmed that and continues to describe the model as delayed. The Verge offered a more measured assessment: the departures and model delays are serious, but Google retains enormous advantages through Search, Workspace, Android, Cloud, custom AI chips and consumer distribution. Google says the Gemini app has surpassed 950 million monthly users, giving it a reach that does not depend entirely on owning the highest-scoring model.Current benchmarks similarly depict a company behind the overall leaders but still firmly competitive. Artificial Analysis places Claude Opus 5 at 63 on its overall model Intelligence Index, while Google reports a score of 56 for Gemini 3.7 Flash—an improvement from 52 for 3.6 Flash but not a return to the top. Arena’s early human-preference results are more favorable, provisionally ranking 3.7 Flash ninth overall and eighth for web development. The resulting picture is not that Google has abandoned advanced AI, but that it has become stronger at rapidly shipping efficient Flash models while struggling to deliver the premium flagship required to reclaim broad leadership. Gemini 4 will now serve as the clearest test of whether the leadership reorganization fixes that execution gap.Available now across Google’s developer stackDevelopers can access Gemini 3.7 Flash through the Gemini API in Google AI Studio and Android Studio, as well as Google’s Antigravity environment. Enterprises can deploy it through Gemini Enterprise Agent Platform and Gemini Enterprise, while consumers with Google AI Pro or Ultra subscriptions can access the model through Spark in supported countries.Google is also shipping updated safeguards covering chemical, biological, radiological and nuclear risks and cyber-offense misuse, according to the company.The unusually fast jump from Gemini 3.6 Flash to 3.7 Flash points toward a model development cycle in which algorithmic improvements can reach production products without waiting for a new flagship generation. Ars Technica also highlighted the three-week interval between the two releases, while Google says the techniques behind the update will inform future models.For developers, that faster cadence creates its own operational question. Models can improve quickly, but production teams still have to benchmark new releases against their own repositories, prompts, tool schemas and failure modes before changing a deployment.Gemini 3.7 Flash gives those teams a particularly strong incentive to run that evaluation. Google’s own numbers show major improvements in production coding, web development, document comprehension and workflow automation without claiming leadership everywhere. At its introductory price, Google is effectively betting that developers will value a model that is competitive enough with more expensive systems while being cheap enough to run repeatedly inside agents.Whether that advantage survives the return to full pricing in January will depend less on leaderboard positions than on how reliably 3.7 Flash completes real work.

Every dollar moved from a traditional IRA into a Roth counts as ordinary income on the federal return for that year. For anyone within two years of Medicare eligibility, that income spike can trigger a surcharge adding $1,148 to $6,936 per person in annual costs. Roth conversion transactions surged 41% in the first quarter of 2026 compared with the prior year, according to Fidelity’s retirement analysis, meaning a growing number of pre-retirees may be headed toward that hit.The surcharge is called IRMAA, the Income-Related Monthly Adjustment Amount, and it arrives two full years after the conversion year. Every dollar of a Roth conversion counts as ordinary taxable income in the year it occurs, IRS Publication 590-A confirmed. How a Roth conversion inflates your Medicare premiumsA traditional individual retirement account holder who leaves funds in the account avoids IRMAA risk on that balance entirely, because no conversion triggers taxable income. Crossing a threshold by a single dollar triggers the full surcharge for that tier across every month of the year, Donna LeValley reported at Kiplinger.The surcharge also applies per person on Medicare, so both spouses pay it individually if both are enrolled in the program. “For large conversions, factor in an additional $2,000 to $8,000 or more in annual Medicare costs,” tax advisory firm SDO CPA explained.The 2026 IRMAA thresholds pre-retirees need to trackThe standard 2026 Medicare Part B premium is $202.90 per month, and IRMAA surcharges stack on top of that baseline, the Centers for Medicare & Medicaid Services (CMS) confirmed in its November 2025 announcement. The first cliff begins at a lower income level than many people approaching retirement expect, particularly for single filers.For married couples filing jointly, 2026 IRMAA surcharges begin when modified adjusted income exceeds $218,000, triggering additional Medicare costs. Couples earning $218,000 or less pay no surcharge, with the standard Part B premium set at $202.90 monthly.Related: How does Medicare IRMAA work?Income from $218,001 to $274,000 adds $81.20 monthly for Part B and $14.50 for Part D per person. Single filers face the first IRMAA tier at $109,000 of modified adjusted gross income, up from $106,000 in 2025, a 2.8% inflation adjustment, according to the CMS 2026 fact sheet.Pre-retirees who convert at 63 or 64 face a timing trap because the two-year lookback places conversion income at the point they first enroll in Medicare, Income Lab reported.The right annual amount “is the one that fits your tax bracket and your IRMAA comfort level,” certified financial planner James Brewer wrote in Forbes.Traditional IRA holders face a slower version of the same trapSomeone who keeps $500,000 in a traditional IRA and begins required minimum distributions at 73 sees taxable income grow at a measured, predictable pace, IRS Publication 590-B showed. A required minimum distribution alone rarely triggers IRMAA, but Social Security, pension income, and part-time earnings can push total Modified Adjusted Gross Income (MAGI) past the $109,000 single-filer cliff by the late 70s.Andy Barton, a certified financial planner at Boldin Advisors, explained in a Boldin Q&A session that pre-retirees often misunderstand when the IRMAA lookback period begins applying to their income decisions.More Medicare/Medicaid:Medicaid’s 5-year rule catches families off guardMedicare goes after the hospital markup you’ve paid for yearsMedicare’s new $50 GLP-1 deal has a catch most overlook”The thing to remember about IRMAA is that it’s not based on your current year of income. It has a 2-year income look-back in it,” Barton said. “So, if you’re on Medicare today, in 2026, they’re actually looking at income from 2024 in order to determine today’s IRMAA amount.”The key difference is control: a Roth converter chooses the year and the amount, making IRMAA exposure more predictable. A traditional IRA holder who defers that decision hands the timing to the RMD schedule, where the annual taxable amount is mandatory and grows whether markets cooperate or not.How to size each year’s conversion around the IRMAA cliffThe fill-the-bracket approach that many planners use for Roth conversions can backfire when the IRMAA threshold sits below the top of your tax bracket. For a married couple with $170,000 in base income, the 24% bracket extends to $403,550, but the first IRMAA cliff arrives at $218,000, based on CMS data.Converting $48,000 fills the gap between base income and the IRMAA line without triggering any surcharges on either spouse’s premiums. A $150,000 conversion would push the couple’s MAGI to $320,000, landing them in the $274,001–$342,000 IRMAA tier at roughly $5,770 per year in additional Medicare surcharges.Roth conversion planning requires annual recalibration rather than a one-time calculation, certified financial planner Chris Reddick of Chris Reddick Financial Planning explained. Reddick’s framework treats each annual conversion amount as constrained by two ceilings, the federal tax bracket and the next IRMAA tier, with the lower of the two setting the conversion ceiling.

The 2026 IRMAA thresholds could raise Medicare costs sharply, making retirement income and Roth conversion timing critical for pre-retirees.PeopleImages / Getty Images

The surcharge is a variable, not an afterthought Reddick noted that the math behind a Roth conversion changes from age 63 to age 66, as Medicare premiums and required minimum distributions alter your income each year. A single year of first-tier surcharges can still net out positive against decades of distribution-year taxes, a trade-off that Brewer’s Forbes IRMAA framework treats as the comparison retirees should make explicit.Reddick’s and Brewer’s analyses converge on one point: the IRMAA surcharge belongs inside the conversion model itself, not as a post-conversion surprise.Related: IRMAA hits retirees two years after property sale

The thesis is that high yields on long-term U.S. Treasuries make non-yielding assets like bitcoin less attractive.

Well, it’s finally happening. Capital One is migrating Discover customers over to its platform.

After the merger was finalized in 2025, Capital One began transitioning Discover customers in 2026 and is expected to complete the process sometime in 2027.

That means many Discover credit card holders have begun receiving notifications about the impending removal of their access to the Discover app and website. And with that comes the removal of some popular Discover perks.

For many, it’s a frustrating and potentially confusing transition that they didn’t ask for when they signed up for their accounts.

In this article, I’m going to walk you through some of the important things to know if you’re going through this account transition.

Table of Contents

Timeline and How the Migration Works

Discover Migration: What Will Change? What Will Stay the Same?

What You Can Do Now

Timeline and How the Migration Works

Capital One has been moving Discover customers to its platform in waves. This transition period began in Summer 2026 and is expected to conclude sometime in 2027.

So, if you’re a Discover customer who has not already received an email notification about your account becoming a Capital One account, you likely can expect to receive one in the near future.

If you have multiple Discover products (e.g., credit card, debit card, savings account, checking account), note that they won’t all migrate on the same timeline.

It appears that credit card accounts started migrating before bank accounts, so those are likely to be moved first.

The migration has been laid out as follows:

Capital One notifies you via email that you’re a part of the next “group” to be phased out of the Discover ecosystem. Personally, I received my Discover card notification on July 31, 2026, with a transition date of October 19, 2026.

After you receive your notice, you will still have temporary, limited functionality on the Discover site and app for tasks like paying bills and redeeming rewards.

In the days leading up to your migration date, you will receive instructions to set up your login on the Capital One site and app.

After the migration date, you will manage the account exclusively via the Capital One website and app. Discover will no longer support your migrated accounts.

Discover Migration: What Will Change? What Will Stay the Same?

If you have a Discover credit card or bank account, you may have some questions about the future of the perks and rewards that you have enjoyed with Discover.

Capital One has provided an FAQ landing page for Discover cardholders that may directly address some of your specific concerns, but I wanted to call out some of the highlights of what you can expect to change and what will stay the same.

Key Changes

You’ll access your account and pay your bill on the Capital One website or app. Your Discover login credentials will eventually be retired and will be useless post-migration.

You’ll lose your free credit score service from Discover, but there is a way to get a free credit score through Capital One’s CreditWise program. You’ll have to enroll after the migration.

Rewards cannot be applied toward your minimum credit card payment anymore. You can still redeem them as a statement credit to reduce your overall balance, though.

You won’t be able to pay with your rewards via Apple Pay anymore. Also, Apple Pay recurring subscriptions may need to be re-established.

Capital One has already removed the Online Privacy Protection perk that offered Discover cardholders free monitoring and removal requests for their name and address from third-party websites. This was one of money expert Clark Howard’s favorite “freebie” credit card perks before it met its demise.

One more to monitor is your credit card’s APR. Capital One says the following about potential changes to those in the FAQ:

“You will receive Account Terms by email or mail, if you haven’t already, alongside other important information from Capital One that outlines your APR—that’s the best place to look because APR varies from cardholder to cardholder.”

What Stays The Same

While there are some minor, but legitimate, gripes about some of the changes above, most of the attributes of your Discover card actually will remain the same.

That includes:

Your card number and details will remain the same. Capital One says: “Primary cardholders can continue to use their card, now and after their account moves to Capital One. Additionally, places where a primary cardholder has their current 16-digit card number stored online will continue to work.” Authorized users will be provided new cards with new numbers, though.

No new annual fees. Discover’s big pitch on its cards was that there were no annual fees and Capital One intends to honor that.

No new account logged with the credit bureau or direct impact to your credit score based on this change. Your credit history from Discover will transfer over.

Your rewards program will stay the same. So, if you have the Discover it Card, you can expect to continue to see rotating 5% categories with spending caps and a non-bonus rewards rate of 1% back on everyday purchases. Existing rewards will transfer as part of the migration.

The popular “cashback match” welcome bonus promotion is set to continue.

What You Can Do Now

Like it or not, all Discover cardholders are soon to be Capital One cardholders.

Some steps you can take to make this migration as smooth as possible include:

Make sure your contact information is current with Discover so it moves over properly

Download the Capital One app in preparation for usage

Redeem your Discover cash back rewards before the limited functionality period begins for your migration

Verify your payment source and any sort of autopay setup transfers over properly

Enroll in CreditWise to continue to enjoy a free credit score with your card

Watch for official emails from Capital One to give you specific instructions (don’t just rely on internet fodder about the changes)

Have you gone through the Discover migration already? We’d love to hear about your experience moving to Capital One in the Clark.com community.
The post Your Discover Card Is Migrating to Capital One: What to Expect appeared first on Clark Howard.

“The American people deserve to know that the President is not using his office to increase the value of his stock portfolios, rather than working to bring down the cost of groceries,” they wrote.

A first planned video conversation feels easier when the technical setup and basic expectations are handled in advance. A few practical checks reduce distractions and leave more attention for clear, respectful communication.
Prepare Before the Conversation
Before joining a scheduled conversation through a service such as Aveola, review the meeting details, your account profile, and the subjects you intend to discuss. Early preparation prevents last-minute searches for links, passwords, headphones, or background information.
Confirm the Time and Access
Check the date, time zone, expected duration, and correct access link. Add the appointment to a calendar with a reminder, then open the platform early enough to complete any sign-in or permission requests.
Confirm that your email address or phone number is verified when the service requires account verification. Use a unique password and activate two-factor authentication when that option is available.
Plan a Few Topics
Prepare two or three simple subjects that fit the reason for the conversation. For a professional call, these subjects might include responsibilities, project goals, or next steps. For a social discussion, hobbies, travel, books, music, or daily routines provide comfortable starting points. Avoid writing a full script. Short notes keep the exchange natural while giving you a reference if the discussion pauses.
Check Your Connection
A stable internet connection supports clearer sound and smoother video. Close large downloads, cloud backups, streaming services, and unused browser tabs before joining.
The table identifies common connection issues and practical responses:

Issue

Visible effect

Preparation step

Weak Wi-Fi signal

Frozen picture

Move closer to the router

Busy home network

Delayed sound

Pause other high-bandwidth activity

Outdated browser

Missing features

Install the current version

Low device power

Sudden disconnection

Charge the device beforehand

Set Up a Comfortable Space
The physical environment affects how clearly both people see and hear each other. Camera placement, light, sound, privacy controls, and personal limits deserve separate attention before the conversation begins.
Position the Camera
Place the camera close to eye level so your face remains centered without requiring you to look sharply upward or downward. A laptop stand, stable box, or adjustable monitor provides a better angle than holding a phone throughout the session.
Leave a small amount of space above your head and keep the lens clean. Look toward the camera while speaking, then return your attention to the screen while listening.
Improve the Lighting
Face a window or place a lamp in front of you, slightly above eye level. Strong light behind your chair creates a silhouette, while overhead lighting alone produces deep shadows around the eyes.
Review the preview screen before joining. Adjust the lamp, curtain, or seat position until facial details appear clear without excessive brightness.
Test the Sound
Use the platform preview or device settings to test the microphone and speakers. Speak at a normal volume and listen for echo, background noise, or distortion. Headphones reduce feedback when speakers sit close to the microphone. A quiet room with curtains, rugs, or soft furniture also limits reflected sound.
Protect Your Privacy
Review what the camera reveals before the conversation begins. Remove documents, photographs, screens, packages, or personal items that display sensitive information.
Five additional checks help protect your account and surroundings:

Disable location details that are unnecessary for the session.
Review camera and microphone permissions in the browser.
Use a background blur when the room contains private material.
Keep account recovery codes outside shared devices.
Sign out after using a borrowed computer or tablet.

Privacy settings also control profile visibility, notifications, and contact options. Read each setting carefully instead of relying on its default value.
Set Personal Boundaries
Decide in advance which subjects and personal details remain outside the discussion. A planned conversation does not require sharing an address, workplace schedule, financial information, private documents, or account credentials.
Set a clear time limit when your schedule requires one. A simple statement at the beginning, such as having 30 minutes available, gives both participants a shared expectation.
Keep the Conversation Comfortable
Preparation continues during the exchange through attentive communication and a calm response to technical interruptions. A small problem with sound or video does not need to disrupt the entire session.
Communicate Respectfully
Speak clearly, allow the other person to finish, and ask direct questions when something is unclear. Muting the microphone during unavoidable background noise keeps the conversation easier to follow. Consent remains relevant throughout live communication. Respect a request to change the topic, pause, disable a feature, or end the session.
Finish With Clear Next Steps
Before leaving, confirm any agreed action, future date, document, or contact method. This step prevents confusion after professional, educational, or project-related discussions.
End the session through the platform controls, close unnecessary tabs, and verify that the camera and microphone are no longer active. A brief review of what worked gives you a stronger routine for the next conversation.
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DeepSeek is expanding beyond the model layer and deeper into the software developers use to put AI agents to work.The Chinese AI lab on Thursday launched the official version of DeepSeek-V4-Pro, an updated flagship model focused heavily on agentic workloads, alongside DeepSeek Harness v0.1, a new open-source agent harness that gives developers an alternative to integrated coding-agent environments such as Anthropic’s Claude Code.Together, the releases amount to a broader developer push from DeepSeek. V4-Pro is now available across DeepSeek’s web interface, mobile app and API, with native support for the OpenAI Responses API and integration with Codex. DeepSeek Harness, meanwhile, is entering developer preview under the MIT license and the code is available now for download and use on GitHub. It’s built around an unusually modular premise: practically every part of the agent runtime can be swapped out as a plugin.But developers accessing V4 through DeepSeek’s API will soon pay considerably more for it. DeepSeek is simultaneously abandoning its existing flat API pricing in favor of peak and off-peak rates beginning at 16:00 UTC on Sunday, Aug. 16 (2 am ET). Even the discounted off-peak cache-miss and output prices will be substantially higher than the prices available today.The combination is significant because DeepSeek is no longer competing solely over model intelligence and token prices. With Harness, it is moving into the layer that determines how models use tools, manipulate files, maintain sessions and execute long-running agent workflows — territory where Anthropic’s Claude Code and other coding agents have become increasingly important developer products.DeepSeek builds its own agent harnessDeepSeek describes Harness, or dsh, as an open-source agent harness built on Cordis, a framework designed around composable plugins.Its guiding principle is simple: “Everything is a plugin.”That extends to models, tools, skills, sessions, sandboxes, filesystems, loops, orchestration and user interfaces, according to DeepSeek. Rather than making those components fixed pieces of a single coding agent, Harness is designed to let developers mix, replace and extend them.The project is available under the MIT license and can currently be launched from npm with npx @deepseek-ai/dsh web. DeepSeek also provides instructions for building it directly from source. The repository describes the software explicitly as a developer preview and warns that “THERE WILL BE COMPATIBILITY-BREAKING CHANGES.”That caveat matters for enterprise developers. Harness is not yet being presented as a stable drop-in production platform. But its architecture points toward a potentially important strategy: DeepSeek can now offer developers not only models but an open framework for assembling the systems that surround them.That makes Anthropic’s Claude Code and OpenAI’s Codex useful competitive references, although the products should not be treated as functionally identical. DeepSeek Harness is an open-source, model-agnostic alternative to the agent infrastructure underlying Claude Code and Codex—not yet a full replacement for either product’s broader developer experience.It can already inspect repositories, edit files, execute shell commands, search files and the web, maintain plans, invoke skills, delegate work to subagents and enforce approval policies. Those are the essential capabilities that make Claude Code and Codex agentic coding tools rather than autocomplete systems. DeepSeek explicitly describes Standard mode as a full coding agent with file editing, shell access, search, planning, subagents and workflows. Its local web interface lets users select a workspace and approve sensitive operations. But Claude Code and Codex now extend well beyond that agent loop. Here’s a quick comparison:DimensionDeepSeek HarnessClaude CodeOpenAI CodexRead, edit and test a repositoryYesYesYesShell and development toolsYesYesYesPlanning and subagentsYesYesYesPermission controls and sandboxingYes, configurable through pluginsYes, mature built-in permission and sandbox systemYes, granular sandbox and approval controlsPrimary interfacesLocal web UI; headless command; Python SDKTerminal, VS Code, JetBrains, desktop, browser, mobile and SlackCLI, IDE extension, desktop app, web/cloud and integrationsHosted background agentsNot documented as a DeepSeek-managed serviceYesYesGitHub-native PR workflowNot documented as a finished integrationGitHub Actions, automatic reviews, issue-to-PR workflowsCloud tasks, automatic reviews, PR fixes and GitHub ActionModel choiceDeepSeek, Anthropic, OpenAI and custom compatible endpointsPrimarily Claude, including Bedrock, Google Cloud and Microsoft hostingPrimarily OpenAI models, with configurable providers in the open-source CLIExtensibilityExceptional: virtually every component is replaceableStrong: skills, hooks, MCP, plugins and agent teamsStrong: skills, MCP, custom agents, SDK and app serverProduct maturityDeveloper preview; breaking changes expectedEstablished commercial productEstablished commercial product plus open-source CLILicenseMITCommercial product with extensibility interfacesCodex CLI is open source; cloud and app services are managed productsDeepSeek Harness instead emphasizes modularity and replacement: the model itself is another plugin rather than necessarily the center of a vertically integrated stack.DeepSeek’s repository was already attracting significant developer attention on launch day, showing roughly 27,500 GitHub stars and 2,000 forks as of Aug. 13, although those rapidly changing figures are best viewed as a snapshot rather than an adoption metric.V4-Pro gets an agent-focused upgradeHarness arrives alongside the general-availability release of DeepSeek-V4-Pro-0813.DeepSeek originally introduced the V4 family in preview in April. The lineup consists of the 1.6-trillion-parameter V4-Pro, with 49 billion parameters activated per token, and the smaller 284-billion-parameter V4-Flash, with 13 billion activated. Both support context windows of up to one million tokens.The company’s Aug. 13 release therefore is not the first appearance of V4-Pro. It is the transition from the earlier preview into an updated official version, with DeepSeek emphasizing agent performance.“The official version of DeepSeek-V4-Pro has been released, featuring significantly enhanced agent capabilities and support for the Responses API and Codex integration,” DeepSeek says on its API website. “It is now fully available across the web, mobile app, and API; we welcome your testing and feedback.”DeepSeek’s changelog similarly says the general-availability model has “significantly enhanced Agent capabilities,” particularly in production environments. Developers using the API do not have to change model identifiers: deepseek-v4-pro now resolves to the latest V4-Pro version.The company has also added native OpenAI Responses API support, lowering the amount of integration work required for applications already built around that interface. DeepSeek says V4-Pro is optimized for OpenAI’s own open source harness, Codex, with one-click setup. Its current API documentation lists Responses API, tool calling, JSON output and an Anthropic-format API among the supported interfaces for both V4-Pro and V4-Flash.For developers using DeepSeek directly rather than through an API, V4-Pro is now accessible through “Expert Mode” on the company’s app and website.Reasoning effort becomes another deployment knobDeepSeek is also making reasoning effort an explicit control across V4-Pro and V4-Flash.The V4 model documentation describes three levels: Non-think, designed for fast routine tasks; Think High, intended for more complex problem-solving and planning; and Think Max, which allocates substantially more reasoning to difficult problems.That distinction can be operationally important for agent systems because maximum reasoning on every step can consume unnecessary time and tokens. A coding agent might use relatively little reasoning to inspect a file or execute a routine tool call, then increase effort when diagnosing a difficult bug or planning a multi-stage code change.DeepSeek’s latest benchmark table suggests the 0813 model improves substantially on agent-oriented tests, although the figures are company-reported and some results depend on the harness configuration.DeepSeek reports V4-Pro-0813 scores of 87.9 on Terminal Bench 2.1, 74.1 on Toolathlon-Verified, 71.1 on DSBench-FullStack and 67.2 on DSBench-Hard. It does not lead every comparison in DeepSeek’s own table: Fable 5, for example, scores 77.9 on Toolathlon-Verified and 77.2 on DSBench-FullStack.There is an especially important qualification buried beneath the benchmark table. For public Code Agent tasks, DeepSeek says V4-Pro-0813 was tested using its upcoming DeepSeek Harness in “minimal mode.”In other words, some of the agent results arriving alongside Harness are not purely model benchmarks. They measure the model operating inside an agent execution environment — precisely the software layer DeepSeek is now releasing to developers.A sharp reversal in DeepSeek’s API price trajectoryThe bigger immediate change for teams already running DeepSeek in production may be pricing.DeepSeek’s current API documentation lists V4-Flash at $0.14 per million cache-miss input tokens and $0.28 per million output tokens, while V4-Pro costs $0.435 for cache-miss input and $0.87 for output. Cache hits are dramatically cheaper at $0.0028 for Flash and $0.003625 for Pro.Those prices themselves represented a major reduction from V4’s original April launch economics. When V4 arrived in April, V4-Pro was priced at $1.74 per million cache-miss input tokens and $3.48 per million output tokens. By late May, DeepSeek had made a 75% reduction permanent, intensifying its position as an unusually inexpensive option for high-volume agent workloads. Now the pendulum is moving in the other direction.Beginning Aug. 16 at 16:00 UTC, DeepSeek will charge different rates depending on when API calls occur. Peak hours are 01:00–04:00 UTC and 06:00–10:00 UTC (9:00 PM – 12:00 AM ET and 2:00 AM – 6:00 AM ET, respectively) with all other hours classified as off-peak. Off-peak rates are half the corresponding peak prices.For V4-Flash, off-peak cache-miss input rises from $0.14 to $0.22 per million tokens, while output rises from $0.28 to $0.66. During peak hours those rates reach $0.44 input and $1.32 output.V4-Pro moves from $0.435 per million cache-miss input tokens and $0.87 output today to $0.66 and $1.98 off-peak, respectively. Peak rates rise to $1.32 input and $3.96 output.The increases are even more pronounced for cached input. V4-Pro cache hits rise from $0.003625 per million tokens today to $0.022 off-peak and $0.044 at peak. Flash moves from $0.0028 to $0.007 off-peak and $0.014 peak.ModelOld input (per 1M token)Old output (per 1M tok)Old total (1M in/1M out)deepseek-v4-flash$0.14$0.28$0.42deepseek-v4-pro$0.435$0.87$1.305The new prices still position DeepSeek as an affordable alternative via API to Western proprietary labs, but Reuters reported Thursday that, depending on model, token category and time of use, the changes represent increases ranging from 50% to more than 1,100% over existing rates.ModelInput ($/1M)Output ($/1M)Total ($/1M)SourceMuse Spark 1.2 Contributor$0.10$0.20$0.30MetaMiMo-V2.5 Flash$0.10$0.30$0.40XiaomiDeepSeek-V4-Flash — off-peak$0.22$0.66$0.88DeepSeekGPT-5.6 Luna$0.20$1.20$1.40OpenAIMiniMax-M3$0.30$1.20$1.50MiniMaxLongCat-2.0 — limited-time promo$0.30$1.20$1.50LongCatDeepSeek-V4-Flash — peak hours$0.44$1.32$1.76DeepSeekMiMo-V2.5$0.40$2.00$2.40XiaomiDeepSeek-V4-Pro — off-peak$0.66$1.98$2.64DeepSeekLongCat-2.0 — standard$0.75$2.95$3.70LongCatMiMo-V2.5 Pro (≤256K)$1.00$3.00$4.00XiaomiDeepSeek-V4-Pro — peak hours$1.32$3.96$5.28DeepSeekMuse Spark 1.1 / 1.2$1.25$4.25$5.50MetaGLM-5.2$1.40$4.40$5.80Z.aiGrok 4.6 — 256K)$2.00$6.00$8.00XiaomiQwen3.8-Max$2.00$6.00$8.00QwenCloudGemini 3.6 Flash$1.50$7.50$9.00GoogleGPT-5.6 Terra$2.00$12.00$14.00OpenAIGrok 4.6 — ≥200K prompt tokens$4.00$12.00$16.00xAIGPT-5.4$2.50$15.00$17.50OpenAIKimi K3$3.00$15.00$18.00Moonshot AIClaude Opus 5$5.00$25.00$30.00AnthropicSakana Fugu Ultra (≤272K)$5.00$30.00$35.00Sakana AIGPT-5.6 Sol — Standard mode$5.00$30.00$35.00OpenAIClaude Fable 5 / Claude Mythos 5$10.00$50.00$60.00AnthropicGPT-5.6 Sol — Fast mode$10.00$60.00$70.00OpenAIThat makes the “50% lower” off-peak framing potentially misleading without context. Off-peak is 50% cheaper than DeepSeek’s new peak rate; it is not a 50% discount from the API prices developers are paying today.For a simple workload consisting of one million cache-miss input tokens plus one million output tokens, V4-Pro currently costs $1.305. The same token mix will cost $2.64 off-peak, roughly twice as much, or $5.28 during peak hours, more than four times the current price.V4-Flash moves from $0.42 under the same simple calculation to $0.88 off-peak and $1.76 peak.Actual application costs will vary considerably depending on the ratio of cached input, uncached input and generated output, making those combined figures illustrative rather than universal total-cost estimates.DeepSeek is moving up the agent stackThe timing makes the strategic direction difficult to miss.When DeepSeek released the V4 preview on April 24, the major story was how much frontier-class capability the company could deliver with an unusually efficient architecture. V4-Pro uses a hybrid attention design combining Compressed Sparse Attention and Heavily Compressed Attention; at a one-million-token context, DeepSeek says it requires only 27% of the single-token inference FLOPs and 10% of the KV cache required by V3.2.By late May, the discussion had shifted toward what those efficiencies meant economically for high-volume agents, whose repeated context reads can make caching a major component of inference costs. DeepSeek’s steep V4 price cuts amplified that advantage.The Aug. 13 releases move the competition another layer upward.DeepSeek now has an updated V4-Pro tuned around agent workloads, standardized interfaces designed to make it easier to connect with existing developer tooling, configurable reasoning effort, and an MIT-licensed harness for controlling the models, tools, sandboxes, filesystems and orchestration surrounding an agent.At the same time, DeepSeek is demonstrating that developers cannot assume its aggressively low API rates are permanent. For organizations considering the platform, workload scheduling, caching behavior and the option to run open weights on their own infrastructure now become more important parts of the total-cost calculation.That leaves DeepSeek pursuing two potentially conflicting advantages at once: making its agent stack more accessible and open while making its own hosted API considerably more expensive.For enterprise developers, Harness may ultimately be the more consequential part of Thursday’s announcement. Models can increasingly be swapped behind standardized interfaces. The harness that controls how an agent reasons, invokes tools, edits software and persists across a workflow can be much harder to replace.DeepSeek is now competing for that layer, too.